Metal organic frameworks (MOFs) have unique advantages in adsorption and preconcentration of heavy metal ions due to their structure and composition characteristics, which make them show great potential in optical sensing of heavy metal ions. However, their applications in the field of electrochemical sensing is greatly limited because of their poor conductivity. In this work, a functionalized MOF composite, thermally reduced graphene oxide-Au nanoparticles-zeolitic imidazolate skeleton material (RGO-Au-ZIF-8), was fabricated. It exhibits much improved electrochemical properties compared with the pristine MOF. A novel electrochemical sensing platform was constructed based on it, and simultaneous detection of lead ions (Pb 2+) and copper ions (Cu 2+) in aqueous solution was realized. Specifically, the Au-ZIF-8 was prepared by adding polyvinylpyrrolidone (PVP)-stabilized Au nanoparticles (AuNPs) to the reaction solution of ZIF-8. The modification of AuNPs effectively improved the conductivity of the material. After compounding with RGO, the RGO-Au-ZIF-8 composite was prepared. The RGO was used as scaffold for the Au-ZIF-8 in the composite to increase the effective surface area of electrode and improve conductivity. The morphology and structure of the prepared materials were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM) and UV-visible absorption spectroscopy (UV-Vis). The electrochemical properties of the modified electrodes were characterized by various electrochemical techniques. The experimental parameters, such as pH value of working solution, accumulation potential, accumulation time and composition ratio of Au-ZIF-8 to RGO were optimized. Under the optimized conditions, simultaneous and sensitive detection of Pb 2+ and Cu 2+ on the prepared electrochemical sensor was realized with the detection limits of 2.6×10-9 and 7.8×10-9 mol•L-1 for Pb 2+ and Cu 2+ , respectively (S/N=3). The interference test showed that the electrochemical sensor has good selectivity for the detec